Evidence map›Paper›PMID 31315157›Full record

ArticleMedical physics2019

A second-generation virtual-pinhole PET device for enhancing contrast recovery and improving lesion detectability of a whole-body PET/CT scanner.

Jianyong Jiang, Ke Li, Qiang Wang, Kenneth Puterbaugh, John W Young, Stefan B Siegel, Joseph A O'Sullivan, Yuan-Chuan Tai

Open access · greenAbstract read
In one paragraph

Article in Medical physics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.4field-weighted citation impact, top 19% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 17 citations in OpenAlex.

  1. Development of a Prototype AWSM-PET Device for Augmented Whole-Body PET Imaging and Initial Human Study.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2026
    Article
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  4. Review
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  8. Multiplexing Readout for Time-of-Flight (TOF) PET Detectors Using Striplines.IEEE transactions on radiation and plasma medical sciences · 2021
    Article
  9. Augmented Whole-Body Scanning via Magnifying PET.IEEE transactions on medical imaging · 2020
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 2 countries.

Jianyong JiangMallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, 63110, USA.
Ke LiDepartment of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, MO, 63130, USA.
Qiang WangMallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, 63110, USA.
Kenneth PuterbaughMolecular Imaging, Siemens Medical Solutions USA, Inc, Knoxville, TN, 37932, USA.
John W YoungMolecular Imaging, Siemens Medical Solutions USA, Inc, Knoxville, TN, 37932, USA.
Stefan B SiegelMolecular Imaging, Siemens Medical Solutions USA, Inc, Knoxville, TN, 37932, USA.
Joseph A O'SullivanDepartment of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, MO, 63130, USA.
Yuan-Chuan TaiMallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, 63110, USA.
Medical Solutions · GBWashington University in St. Louis · USMallinckrodt (United States) · US

Funding

Translation of virtual-pinhole magnifying PET technology to clinical whole-body cancer imagingR01CA233912 · NCI · WASHINGTON UNIVERSITY · PI TAI, YUAN-CHUAN · 2019 to 2023
$2.6M
A Sub-Millimeter Resolution add-on for Animal PET scannersR01CA136554 · NCI · WASHINGTON UNIVERSITY · PI SIEGEL, STEFAN, TAI, YUAN-CHUAN · 2009 to 2013
$2.1M
Department of Energy DE-SC0005157Mallinckrodt Institute of RadiologyNational Institute of Health R01-CA136554NCI NIH HHS R01 CA136554NCI NIH HHS R01 CA233912
6 · The paper itself

Abstract

purposeWe have developed a second-generation virtual-pinhole (VP) positron emission tomography (PET) device that can position a flat-panel PET detector around a patient's body using a robotic arm to enhance the contrast recovery coefficient (CRC) and detectability of lesions in any region-of-interest using a whole-body PET/computed tomography (CT) scanner.

methodsWe constructed a flat-panel VP-PET device using 32 high-resolution detectors, each containing a 4

resultsThe repeatability in positioning the flat-panel detectors using a robotic arm is better than 0.15 mm in all three directions. Experimental results show that the average CRC of 3.3, 4.3, and 6.0 mm diameter tumors was 0.82%, 2.90%, and 5.25%, respectively, when measured by the native scanner. The corresponding CRC was 2.73%, 6.21% and 10.13% when imaged by the VP-PET insert device with the flat-panel detector under the torso phantom. These values may be further improved to 4.31%, 9.65% and 18.01% by a future dual-panel VP-PET insert device if DOI detectors are employed to triple its detector efficiency. Monte Carlo simulation results show that the tumor detectability can be improved by a VP-PET device that has a single flat-panel detector. The improvement is greater if the VP-PET device employs a dual-panel design.

conclusionsWe have developed a prototype flat-panel VP-PET device and integrated it with a clinical PET/CT scanner. It significantly enhances the contrast of lesions, especially for those that are borderline detectable by the native scanner, within regions-of-interest specified by users. Simulation demonstrated the enhancement in lesion detectability with the VP-PET device. This technology may become a cost-effective solution for organ-specific imaging tasks.

Indexed as

Contrast MediaImage Processing, Computer-AssistedMonte Carlo MethodPositron Emission Tomography Computed TomographyWhole Body ImagingContrast MediaGPUimage reconstructionlesion detectionPET insertvirtual-pinhole PET

Identifiers

PMID31315157
PMCPMC6739194
OpenAlexW2958696211

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.